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ScienceDirect

Available online at

Available online at www.sciencedirect.com

www.sciencedirect.com

ScienceDirect

Energy Procedia 00 (2017) 000–000

www.elsevier.com/locate/procedia

1876-6102 © 2017 The Authors. Published by Elsevier Ltd.

Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling.

The 15th International Symposium on District Heating and Cooling

Assessing the feasibility of using the heat demand-outdoor

temperature function for a long-term district heat demand forecast

I. Andrić

a,b,c

*, A. Pina

a

, P. Ferrão

a

, J. Fournier

b

., B. Lacarrière

c

, O. Le Corre

c aIN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal

bVeolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France

cDépartement Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France

Abstract

District heating networks are commonly addressed in the literature as one of the most effective solutions for decreasing the

greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat

sales. Due to the changed climate conditions and building renovation policies, heat demand in the future could decrease,

prolonging the investment return period.

The main scope of this paper is to assess the feasibility of using the heat demand – outdoor temperature function for heat demand

forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665

buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district

renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were

compared with results from a dynamic heat demand model, previously developed and validated by the authors.

The results showed that when only weather change is considered, the margin of error could be acceptable for some applications

(the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation

scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered).

The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the

decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and

renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the

coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and

improve the accuracy of heat demand estimations.

© 2017 The Authors. Published by Elsevier Ltd.

Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and

Cooling.

Keywords: Heat demand; Forecast; Climate change

Energy Procedia 157 (2019) 180–192

1876-6102 © 2019 The Authors. Published by Elsevier Ltd.

This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18.

10.1016/j.egypro.2018.11.179

Available online at www.sciencedirect.com

ScienceDirect

Energy Procedia 00 (2018) 000–000

www.elsevier.com/locate/procedia

1876-6102 © 2018 The Authors. Published by Elsevier Ltd.

This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18.

Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18,

19–21 September 2018, Athens, Greece

Economic parameters in the evaluation studies focusing on

building energy efficiency: a review of the underlying

rationale, data sources, and assumptions

Sergio Copiello

a

*

aIUAV University of Venice, Dorsoduro 2206, 30123 Venice, Italy

Abstract

A growing literature has highlighted the variables and parameters that most affect the technical feasibility and the

economic viability of the measures meant to improve building energy efficiency. This paper discusses the results of a

literature review, which focuses on the studies that deal with three economic parameters: the price to be paid for the

energy supply, the energy inflation rate, and the discount rate used to convert future cash flows to a present value,

namely, an upfront lump-sum equivalent. A specific co-occurrence analysis of terms is performed on the titles and

abstracts of the examined documents. The representation of the results allows recognizing several significant clusters

and network relationships. Moreover, that literature review enables to identify two well-established research strands.

The first involves the relationship between energy prices and the profitability of efficiency-related investments. The

second research branch points at the pivotal role played by the discount rate when evaluating the investments in

energy-efficient measures.

© 2018 The Authors. Published by Elsevier Ltd.

This is an open access article under the CC BY-NC-ND license (

https://creativecommons.org/licenses/by-nc-nd/4.0/

)

Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy,

Environment and Sustainability, TMREES18.

Keywords: Building energy efficiency; Energy price; Inflation rate; Discount rate

* Corresponding author. Tel.: +39 041 257 1387; fax: +39 041 257 2424. E-mail address: copiello@iuav.it

10.1016/j.egypro.2018.11.179

© 2019 The Authors. Published by Elsevier Ltd.

This is an open access article under the CC BY-NC-ND license (

https://creativecommons.org/licenses/by-nc-nd/4.0/

)

Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy,

Environment and Sustainability, TMREES18.

1876-6102

ScienceDirect

Energy Procedia 00 (2018) 000–000

www.elsevier.com/locate/procedia

1876-6102 © 2018 The Authors. Published by Elsevier Ltd.

This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18.

Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18,

19–21 September 2018, Athens, Greece

Economic parameters in the evaluation studies focusing on

building energy efficiency: a review of the underlying

rationale, data sources, and assumptions

Sergio Copiello

a

*

aIUAV University of Venice, Dorsoduro 2206, 30123 Venice, Italy

Abstract

A growing literature has highlighted the variables and parameters that most affect the technical feasibility and the

economic viability of the measures meant to improve building energy efficiency. This paper discusses the results of a

literature review, which focuses on the studies that deal with three economic parameters: the price to be paid for the

energy supply, the energy inflation rate, and the discount rate used to convert future cash flows to a present value,

namely, an upfront lump-sum equivalent. A specific co-occurrence analysis of terms is performed on the titles and

abstracts of the examined documents. The representation of the results allows recognizing several significant clusters

and network relationships. Moreover, that literature review enables to identify two well-established research strands.

The first involves the relationship between energy prices and the profitability of efficiency-related investments. The

second research branch points at the pivotal role played by the discount rate when evaluating the investments in

energy-efficient measures.

© 2018 The Authors. Published by Elsevier Ltd.

This is an open access article under the CC BY-NC-ND license (

https://creativecommons.org/licenses/by-nc-nd/4.0/

)

Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy,

Environment and Sustainability, TMREES18.

Keywords: Building energy efficiency; Energy price; Inflation rate; Discount rate

* Corresponding author. Tel.: +39 041 257 1387; fax: +39 041 257 2424. E-mail address: copiello@iuav.it

2 Sergio Copiello / Energy Procedia 00 (2018) 000–000

1. Introduction

The issue of building energy efficiency has gained interest during the last years and, more broadly, over a time

span of four decades or so [

1] (Fig. 1

). Energy efficiency is a prominent topic on the agenda due to the need of taking

fuel consumptions under control and reducing their environmental impact. Under this framework, the construction

sector plays a pivotal role because buildings largely contribute to primary energy demand and consumption, as well

as to greenhouse gas emissions [

2-4]. Concerning the evaluation of the measures aiming at improving building energy

efficiency, a growing literature is available. The results of several field studies, although sometimes conflicting, have

the merit of having highlighted the variables and parameters that most affect the technical feasibility and the economic

viability of those measures. As far as the latter is concerned, a summary list of the most influential parameters should

include, at least, the following items [

1,5]: contingent and long-term geo-climatic conditions [6,7]; building type and

physical characteristics of the constructions [

8,9]; consumers’ preferences and occupants’ behavior [10-13]; prices of

energy supply and their changes over time [

14-16]; investment costs to be incurred and the corresponding expected

return and payback time [

17-19].

Fig. 1. Growing interest for building energy efficiency (source: Google Ngram Viewer).

This paper aims to present the results of a systematic literature review, with regard to the studies that use economic

parameters to assess the feasibility of energy efficiency measure in the building industry. The literature review

purposely focuses on the following three economic parameters: the price to be paid for the energy supply; the inflation

rate, especially as far as energy sources are concerned; the discount rate used to convert future values to present values,

so to calculate the upfront lump-sum equivalent of the expected cash flows.

The structure of this paper is as follows. The next section describes the source used to gather information and the

method followed to identify the relevant literature. The subsequent paragraph provides an overview of the results,

with specific reference to these issues: topics addressed in the studies, data sources, and estimated values or

assumptions as far as the economic parameters are concerned. A further part of the text is devoted to identify and

discuss two main, well-established research strands: the role played by energy prices in techno-economic evaluations

is the former, the prominence of the discount rate in the same evaluations is the latter. Finally, the last section draws

the conclusions.

2. Method

The literature review discussed in this study is based on bibliographic research, which has been performed using

the indexing and abstracting database Scopus, provided by Elsevier. Although some limitations and other issues are

known to affect the selected source [

20-23], it has been chosen due to its wider coverage in comparison to others such

(2)

Sergio Copiello / Energy Procedia 157 (2019) 180–192 181

Available online at www.sciencedirect.com

ScienceDirect

Energy Procedia 00 (2018) 000–000

www.elsevier.com/locate/procedia

1876-6102 © 2018 The Authors. Published by Elsevier Ltd.

This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18.

Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18,

19–21 September 2018, Athens, Greece

Economic parameters in the evaluation studies focusing on

building energy efficiency: a review of the underlying

rationale, data sources, and assumptions

Sergio Copiello

a

*

aIUAV University of Venice, Dorsoduro 2206, 30123 Venice, Italy

Abstract

A growing literature has highlighted the variables and parameters that most affect the technical feasibility and the

economic viability of the measures meant to improve building energy efficiency. This paper discusses the results of a

literature review, which focuses on the studies that deal with three economic parameters: the price to be paid for the

energy supply, the energy inflation rate, and the discount rate used to convert future cash flows to a present value,

namely, an upfront lump-sum equivalent. A specific co-occurrence analysis of terms is performed on the titles and

abstracts of the examined documents. The representation of the results allows recognizing several significant clusters

and network relationships. Moreover, that literature review enables to identify two well-established research strands.

The first involves the relationship between energy prices and the profitability of efficiency-related investments. The

second research branch points at the pivotal role played by the discount rate when evaluating the investments in

energy-efficient measures.

© 2018 The Authors. Published by Elsevier Ltd.

This is an open access article under the CC BY-NC-ND license (

https://creativecommons.org/licenses/by-nc-nd/4.0/

)

Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy,

Environment and Sustainability, TMREES18.

Keywords: Building energy efficiency; Energy price; Inflation rate; Discount rate

* Corresponding author. Tel.: +39 041 257 1387; fax: +39 041 257 2424. E-mail address: copiello@iuav.it

ScienceDirect

Energy Procedia 00 (2018) 000–000

www.elsevier.com/locate/procedia

1876-6102 © 2018 The Authors. Published by Elsevier Ltd.

This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18.

Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18,

19–21 September 2018, Athens, Greece

Economic parameters in the evaluation studies focusing on

building energy efficiency: a review of the underlying

rationale, data sources, and assumptions

Sergio Copiello

a

*

aIUAV University of Venice, Dorsoduro 2206, 30123 Venice, Italy

Abstract

A growing literature has highlighted the variables and parameters that most affect the technical feasibility and the

economic viability of the measures meant to improve building energy efficiency. This paper discusses the results of a

literature review, which focuses on the studies that deal with three economic parameters: the price to be paid for the

energy supply, the energy inflation rate, and the discount rate used to convert future cash flows to a present value,

namely, an upfront lump-sum equivalent. A specific co-occurrence analysis of terms is performed on the titles and

abstracts of the examined documents. The representation of the results allows recognizing several significant clusters

and network relationships. Moreover, that literature review enables to identify two well-established research strands.

The first involves the relationship between energy prices and the profitability of efficiency-related investments. The

second research branch points at the pivotal role played by the discount rate when evaluating the investments in

energy-efficient measures.

© 2018 The Authors. Published by Elsevier Ltd.

This is an open access article under the CC BY-NC-ND license (

https://creativecommons.org/licenses/by-nc-nd/4.0/

)

Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy,

Environment and Sustainability, TMREES18.

Keywords: Building energy efficiency; Energy price; Inflation rate; Discount rate

* Corresponding author. Tel.: +39 041 257 1387; fax: +39 041 257 2424. E-mail address: copiello@iuav.it

2 Sergio Copiello / Energy Procedia 00 (2018) 000–000

1. Introduction

The issue of building energy efficiency has gained interest during the last years and, more broadly, over a time

span of four decades or so [

1] (Fig. 1

). Energy efficiency is a prominent topic on the agenda due to the need of taking

fuel consumptions under control and reducing their environmental impact. Under this framework, the construction

sector plays a pivotal role because buildings largely contribute to primary energy demand and consumption, as well

as to greenhouse gas emissions [

2-4]. Concerning the evaluation of the measures aiming at improving building energy

efficiency, a growing literature is available. The results of several field studies, although sometimes conflicting, have

the merit of having highlighted the variables and parameters that most affect the technical feasibility and the economic

viability of those measures. As far as the latter is concerned, a summary list of the most influential parameters should

include, at least, the following items [

1,5]: contingent and long-term geo-climatic conditions [6,7]; building type and

physical characteristics of the constructions [

8,9]; consumers’ preferences and occupants’ behavior [10-13]; prices of

energy supply and their changes over time [

14-16]; investment costs to be incurred and the corresponding expected

return and payback time [

17-19].

Fig. 1. Growing interest for building energy efficiency (source: Google Ngram Viewer).

This paper aims to present the results of a systematic literature review, with regard to the studies that use economic

parameters to assess the feasibility of energy efficiency measure in the building industry. The literature review

purposely focuses on the following three economic parameters: the price to be paid for the energy supply; the inflation

rate, especially as far as energy sources are concerned; the discount rate used to convert future values to present values,

so to calculate the upfront lump-sum equivalent of the expected cash flows.

The structure of this paper is as follows. The next section describes the source used to gather information and the

method followed to identify the relevant literature. The subsequent paragraph provides an overview of the results,

with specific reference to these issues: topics addressed in the studies, data sources, and estimated values or

assumptions as far as the economic parameters are concerned. A further part of the text is devoted to identify and

discuss two main, well-established research strands: the role played by energy prices in techno-economic evaluations

is the former, the prominence of the discount rate in the same evaluations is the latter. Finally, the last section draws

the conclusions.

2. Method

The literature review discussed in this study is based on bibliographic research, which has been performed using

the indexing and abstracting database Scopus, provided by Elsevier. Although some limitations and other issues are

known to affect the selected source [

20-23], it has been chosen due to its wider coverage in comparison to others such

(3)

that constitute the focus of this study - namely, energy price, energy inflation rate, and discount rate - the search string

used here is as follows:

( ALL ( “Building energy efficiency” ) AND TITLE-ABS-KEY ( “Energy price” ) OR TITLE-ABS-KEY (

“Inflation rate” ) OR TITLE-ABS-KEY ( “Discount rate” ) ).

In other words, a general key expression (“building energy efficiency”) is adopted to define the boundaries of the

analysis. That key is used to search all the abstracting database fields. In addition, three specific expressions (“energy

price”, “inflation rate”, and “discount rate”) are adopted to refine the search within titles, abstracts, and keywords.

The search returns a result of 65 published items. That number does not reflect the whole amount of studies that,

somehow, make use of the three analyzed parameters. Indeed, several other indexed documents base their analysis on

economic parameters without explicitly reporting them in the abstract or among the keywords. As a case in point, let

us consider that searching for the three key expressions (“energy price”, “inflation rate”, and “discount rate”) in all

the abstracting database fields - without limiting the search to titles, abstracts, and keywords - would produce 188

results. However, I take into account the 65 results of the search string mentioned above relying on the assumption

that mentioning an economic parameter in the abstract or among the keywords reveals that it takes on high significance

in the research work and the related publication.

It deserves mentioning a partial overlap of the results (

Fig. 2

). Although most of the analyzed studies deal only

with the parameter of the energy price or, in a subordinate position, exclusively with the discount rate, a certain number

of publications consider two parameters (i.e., the energy supply cost and the discount rate, or the energy inflation rate

and, again, the discount rate). Other few studies present empirical applications, if not even theoretical reflections,

which involve all the three parameters considered here.

Fig. 2. Summary of the bibliographic search in Scopus.

The items are characterized by a publication window of about two decades, from 1996 to 2018. However, only two

articles date back to the late nineties, while all the other documents have been published after the year 2007. What is

more, nearly 70% of the documents have been authored during the last five years. Concerning the publication venue,

the results are mostly journal articles (72%) and conference papers (23%), while only three (5%) are book chapters.

As far as the publication outlets are concerned, the journal Energy and Buildings hosts nine articles, eight other papers

have been published in Energy Policy, and five each in Energy and Journal of Cleaner Production.

3. Summary of the results

Tables 1 to 4

summarize the results (in chronological order) by reporting, for each study, the publication venue,

the economic parameter(s) considered, and the synthetic description of the topic. Besides, the number of citations (as

of April 2018) is meant to act as a proxy of the attention gained, although a low number of citations is likely to

characterize the studies published in the last couple of years. In absolute terms, the most cited study is that authored

by Newell, Jaffe, and Stavins (test of the Hicks’s induced innovation hypothesis on energy-using consumer durables),

published in 1999 in The Quarterly Journal of Economics [

28]. Other highly-cited documents are those by Zhao, Li,

and Ma (decomposition analysis of urban energy consumptions in China) and by Kumbaroğlu and Madlener

(evaluation of optimal retrofit investment options using Monte Carlo simulation), both published in 2012 [

37,38]. Out

of the 65 analyzed studies, nine are not included in the tables due to their limited relevance, namely, the fact that they

only incidentally deal with at least one of the economic parameters which this study focuses on.

Table 1. Summary of the results (first part). Economic parameter Year First author and

reference Venue (1) Energy price Inflation rate Discount rate Topic Citations 1996 Levine, M.D.

[27] ja x Gap between energy prices and the full costs of energy production due to subsidies, which disincentive investments in energy efficiency

7 1999 Newell, R.G.

[28] ja x The relationship between product innovation and energy price in the field of energy-using consumer durables

377 2008 Scott, M.J. [29] ja x Net savings of the US building energy efficiency

programs considering UN IPCC warming scenarios (reduced need for heating and increase in space cooling demand)

12

2009 Cao, J. [30] ja x Influence of the energy price on the economic viability of a retrofit measure, showing that contradictions affect China’s energy price system

9 2009 Wu, Y. [31] cp x Energy prices are among the parameters to consider for

the building energy management to be effective and efficient

2 2010 Parfomak, P.W.

[32] bc x Policies need to address the energy price risks: uncertainty about future energy prices hinders the assumption of investment decisions about building efficiency

0

2010 Zwettler, G.

[33] cp x Energy costs are among the parameter considered in an optimization software meant to assist the design of energy efficient buildings

2 2011 Jeong, J. [34] ja x Heating energy usage patterns in the light of the

substitute/complementary relationship between gas and electricity and according to energy price and household characteristics

13

2011 Ouyang, J. [14] ja x x x Life cycle cost analysis on the upgrade of aging residential buildings in China, it is shown that growing energy prices and subsidies do not lead to a satisfactory economic viability

19

2011 Parfomak, P.W.

[35] bc x [see above the item 2010, Parfomak, P.W.] 0

2012 Haney, A.B.

[36] bc x International comparisons of demand-side management strategies and policies to improve energy efficiency, and their relationships with energy prices

6 2012 Zhao, X. [37] ja x Decomposition of China’s residential energy use,

showing that consumptions are shifting towards a more energy-intensive model and price reforms contribute to energy savings

83

(4)

that constitute the focus of this study - namely, energy price, energy inflation rate, and discount rate - the search string

used here is as follows:

( ALL ( “Building energy efficiency” ) AND TITLE-ABS-KEY ( “Energy price” ) OR TITLE-ABS-KEY (

“Inflation rate” ) OR TITLE-ABS-KEY ( “Discount rate” ) ).

In other words, a general key expression (“building energy efficiency”) is adopted to define the boundaries of the

analysis. That key is used to search all the abstracting database fields. In addition, three specific expressions (“energy

price”, “inflation rate”, and “discount rate”) are adopted to refine the search within titles, abstracts, and keywords.

The search returns a result of 65 published items. That number does not reflect the whole amount of studies that,

somehow, make use of the three analyzed parameters. Indeed, several other indexed documents base their analysis on

economic parameters without explicitly reporting them in the abstract or among the keywords. As a case in point, let

us consider that searching for the three key expressions (“energy price”, “inflation rate”, and “discount rate”) in all

the abstracting database fields - without limiting the search to titles, abstracts, and keywords - would produce 188

results. However, I take into account the 65 results of the search string mentioned above relying on the assumption

that mentioning an economic parameter in the abstract or among the keywords reveals that it takes on high significance

in the research work and the related publication.

It deserves mentioning a partial overlap of the results (

Fig. 2

). Although most of the analyzed studies deal only

with the parameter of the energy price or, in a subordinate position, exclusively with the discount rate, a certain number

of publications consider two parameters (i.e., the energy supply cost and the discount rate, or the energy inflation rate

and, again, the discount rate). Other few studies present empirical applications, if not even theoretical reflections,

which involve all the three parameters considered here.

Fig. 2. Summary of the bibliographic search in Scopus.

The items are characterized by a publication window of about two decades, from 1996 to 2018. However, only two

articles date back to the late nineties, while all the other documents have been published after the year 2007. What is

more, nearly 70% of the documents have been authored during the last five years. Concerning the publication venue,

the results are mostly journal articles (72%) and conference papers (23%), while only three (5%) are book chapters.

As far as the publication outlets are concerned, the journal Energy and Buildings hosts nine articles, eight other papers

have been published in Energy Policy, and five each in Energy and Journal of Cleaner Production.

3. Summary of the results

Tables 1 to 4

summarize the results (in chronological order) by reporting, for each study, the publication venue,

the economic parameter(s) considered, and the synthetic description of the topic. Besides, the number of citations (as

of April 2018) is meant to act as a proxy of the attention gained, although a low number of citations is likely to

characterize the studies published in the last couple of years. In absolute terms, the most cited study is that authored

by Newell, Jaffe, and Stavins (test of the Hicks’s induced innovation hypothesis on energy-using consumer durables),

published in 1999 in The Quarterly Journal of Economics [

28]. Other highly-cited documents are those by Zhao, Li,

and Ma (decomposition analysis of urban energy consumptions in China) and by Kumbaroğlu and Madlener

(evaluation of optimal retrofit investment options using Monte Carlo simulation), both published in 2012 [

37,38]. Out

of the 65 analyzed studies, nine are not included in the tables due to their limited relevance, namely, the fact that they

only incidentally deal with at least one of the economic parameters which this study focuses on.

Table 1. Summary of the results (first part). Economic parameter Year First author and

reference Venue (1) Energy price Inflation rate Discount rate Topic Citations 1996 Levine, M.D.

[27] ja x Gap between energy prices and the full costs of energy production due to subsidies, which disincentive investments in energy efficiency

7 1999 Newell, R.G.

[28] ja x The relationship between product innovation and energy price in the field of energy-using consumer durables

377 2008 Scott, M.J. [29] ja x Net savings of the US building energy efficiency

programs considering UN IPCC warming scenarios (reduced need for heating and increase in space cooling demand)

12

2009 Cao, J. [30] ja x Influence of the energy price on the economic viability of a retrofit measure, showing that contradictions affect China’s energy price system

9 2009 Wu, Y. [31] cp x Energy prices are among the parameters to consider for

the building energy management to be effective and efficient

2 2010 Parfomak, P.W.

[32] bc x Policies need to address the energy price risks: uncertainty about future energy prices hinders the assumption of investment decisions about building efficiency

0

2010 Zwettler, G.

[33] cp x Energy costs are among the parameter considered in an optimization software meant to assist the design of energy efficient buildings

2 2011 Jeong, J. [34] ja x Heating energy usage patterns in the light of the

substitute/complementary relationship between gas and electricity and according to energy price and household characteristics

13

2011 Ouyang, J. [14] ja x x x Life cycle cost analysis on the upgrade of aging residential buildings in China, it is shown that growing energy prices and subsidies do not lead to a satisfactory economic viability

19

2011 Parfomak, P.W.

[35] bc x [see above the item 2010, Parfomak, P.W.] 0

2012 Haney, A.B.

[36] bc x International comparisons of demand-side management strategies and policies to improve energy efficiency, and their relationships with energy prices

6 2012 Zhao, X. [37] ja x Decomposition of China’s residential energy use,

showing that consumptions are shifting towards a more energy-intensive model and price reforms contribute to energy savings

83

(5)

Table 2. Summary of the results (second part). Economic parameter Year First author and

reference Venue (1) Energy price Inflation rate Discount rate Topic Citations 2012 Kumbaroglu, G.

[38] ja x x Case study of building retrofit addressing uncertainty in energy prices through Monte Carlo simulation, showing that their changes significantly affect the profitability of the investments

66

2013 Cajias, M. [39] ja x Financial performance of German housing: energy efficiency affects tenant decisions (0.76 Eur/m2 higher rent) and the performance of investor portfolios (up to 3.15% higher return)

30

2013 Cox, M. [40] ja x Revision of the projected investments in energy-efficient equipment and related energy consumptions in the US according to different levels of the discount rate

16

2013 Egging, R. [41] ja x Discussion on the drivers and uncertainties in the recent and future energy market trends, especially as far as energy prices are concerned

6 2014 Wu, W. [42] ja x Techno-economic analysis of a combined heat supply

system, linking heating period, energy price, and payback period

11 2014 Deng, Q. [43] ja x Analysis and discussion of a simulation-based decision

model to design contract period in the field of Energy Performance Contracting

17 2014 Yan, X. [44] ja x x Techno-economic analysis of energy storage systems:

the sensitivity analysis reveals that the discount rate has the largest influence on the viability of the analyzed systems

20

2014 Qian, D. [45] ja x x Development of a revenue-sharing bargaining model within Energy Performance Contracting and analysis of the impacts of energy prices and risk-adjusted discount rates

16

2014 Bonakdar, F.

[46] ja x x Analysis of the cost-optimum level of renovation in a multi-story residential building according to different discount rates and energy prices

19 2014 Adika, C.O.

[47] ja x Approach to the development of an automated appliance scheduling system for household energy management including expected energy prices

81 2015 Guo, L. [48] cp x Optimization methodology to minimize the energy cost

under energy price uncertainty: random price changes with a known underlying distribution

2 2015 Wu, L. [49] ja x Environmental, economic analysis of a water supply

facility incorporating climate externalities: a higher discount rate counteracts the effectiveness of the carbon cost factor

8

2015 Lin, B. [50] ja x Analysis of building energy consumptions and building energy efficiency in light of urbanization process and energy price trends

32 2015 Deng, Q. [51] ja x x x Energy cost savings model, meant to improve Energy

Performance Contracting, which accounts for energy price fluctuation using Monte Carlo simulation

14 2015 Deng, Q. [52] ja x Simulation-based model to maximize the facility

owner’s profit and satisfy the ESCo’s expected rate of return

7 (1) ja: journal article; cp: conference paper; bc: book chapter.

Table 3. Summary of the results (third part). Economic parameter Year First author Venue

(1) Energy price Inflation rate Discount rate Topic Citations 2015 Lin, B. [53] ja x Analysis of the substitution relationship between each

input factor including energy in China’s food industry, showing that a direct rebound effect partially offsets energy savings

4

2016 Lin, B. [54] ja x Analysis of energy rebound effect in China’s light industry considering the effects of energy prices on energy consumptions

11 2016 Roshchanka, V.

[55] ja x Feedbacks about the use of Energy Performance Contracts and the development of the ESCos’ business model in the Russian Federation

4 2016 Liu, X. [56] ja x Model meant to determine the optimal value of the

discount rate that enables to take emissions under controls in building procurement contracts

0 2016 Ameer, B. [57] ja x x Impact of heavily subsidized energy prices for the

residential building sector in Kuwait: need to increase the electricity price to improve energy savings and efficiency in building

8

2016 Good, N. [58] ja x Techno-economic framework for the assessment of business cases of low carbon technologies, with a focus on multiple energy systems and vectors

19 2016 Krarti, M. [59] ja x x Analysis of the cost-effectiveness potential of net-zero

energy residential buildings in the Middle East and North Africa region, which is found to strongly depends on energy prices

11

2016 Brandão de Vasconcelos, A. [60]

ja x Cost-optimal analysis of several refurbishment

scenarios accounting for different discount rate using sensitivity analysis

3 2016 Liu, H. [61] ja x Analysis of the impacts of technological advancement

on energy consumption in China’s building industry in light of the direct rebound effect

6 2016 He, L. [62] ja x Analysis to test the hypothesis that the relative energy

price and not the absolute one is the most important to explain energy consumptions

1 2017 Miezis, M. [63] cp x Algorithm for model predictive control (MPC) in

multi-family buildings, including energy prices as constraints, with application to a case study in Latvia

3 2017 Copiello, S. [1] ja x Review of the paradoxes affecting the research topics

focusing on building energy efficiency, one of which relates to the relationship between investments and energy prices

14

2017 Khabdullin, A.

[64] cp x Analysis of the possible use of electricity as a source for district heating systems considering electricity price in comparison with heat energy price

0 2017 Krarti, M. [65] ja x x Evaluation of economic and environmental impacts of

energy efficiency programs for new and existing buildings in Saudi Arabia under conditions of highly subsidized energy prices

1

2017 Weeber, M.

[66] cp x Overview and discussion of opportunities, risks, and trends associated with the topic of energy flexibility in a context of fluctuating energy prices

0 2017 Simona, P.L.

[67] cp x Study on increasing energy efficiency in collective residential buildings by acting on their thermal insulation

0 (1) ja: journal article; cp: conference paper; bc: book chapter.

(6)

Table 2. Summary of the results (second part). Economic parameter Year First author and

reference Venue (1) Energy price Inflation rate Discount rate Topic Citations 2012 Kumbaroglu, G.

[38] ja x x Case study of building retrofit addressing uncertainty in energy prices through Monte Carlo simulation, showing that their changes significantly affect the profitability of the investments

66

2013 Cajias, M. [39] ja x Financial performance of German housing: energy efficiency affects tenant decisions (0.76 Eur/m2 higher rent) and the performance of investor portfolios (up to 3.15% higher return)

30

2013 Cox, M. [40] ja x Revision of the projected investments in energy-efficient equipment and related energy consumptions in the US according to different levels of the discount rate

16

2013 Egging, R. [41] ja x Discussion on the drivers and uncertainties in the recent and future energy market trends, especially as far as energy prices are concerned

6 2014 Wu, W. [42] ja x Techno-economic analysis of a combined heat supply

system, linking heating period, energy price, and payback period

11 2014 Deng, Q. [43] ja x Analysis and discussion of a simulation-based decision

model to design contract period in the field of Energy Performance Contracting

17 2014 Yan, X. [44] ja x x Techno-economic analysis of energy storage systems:

the sensitivity analysis reveals that the discount rate has the largest influence on the viability of the analyzed systems

20

2014 Qian, D. [45] ja x x Development of a revenue-sharing bargaining model within Energy Performance Contracting and analysis of the impacts of energy prices and risk-adjusted discount rates

16

2014 Bonakdar, F.

[46] ja x x Analysis of the cost-optimum level of renovation in a multi-story residential building according to different discount rates and energy prices

19 2014 Adika, C.O.

[47] ja x Approach to the development of an automated appliance scheduling system for household energy management including expected energy prices

81 2015 Guo, L. [48] cp x Optimization methodology to minimize the energy cost

under energy price uncertainty: random price changes with a known underlying distribution

2 2015 Wu, L. [49] ja x Environmental, economic analysis of a water supply

facility incorporating climate externalities: a higher discount rate counteracts the effectiveness of the carbon cost factor

8

2015 Lin, B. [50] ja x Analysis of building energy consumptions and building energy efficiency in light of urbanization process and energy price trends

32 2015 Deng, Q. [51] ja x x x Energy cost savings model, meant to improve Energy

Performance Contracting, which accounts for energy price fluctuation using Monte Carlo simulation

14 2015 Deng, Q. [52] ja x Simulation-based model to maximize the facility

owner’s profit and satisfy the ESCo’s expected rate of return

7 (1) ja: journal article; cp: conference paper; bc: book chapter.

Table 3. Summary of the results (third part). Economic parameter Year First author Venue

(1) Energy price Inflation rate Discount rate Topic Citations 2015 Lin, B. [53] ja x Analysis of the substitution relationship between each

input factor including energy in China’s food industry, showing that a direct rebound effect partially offsets energy savings

4

2016 Lin, B. [54] ja x Analysis of energy rebound effect in China’s light industry considering the effects of energy prices on energy consumptions

11 2016 Roshchanka, V.

[55] ja x Feedbacks about the use of Energy Performance Contracts and the development of the ESCos’ business model in the Russian Federation

4 2016 Liu, X. [56] ja x Model meant to determine the optimal value of the

discount rate that enables to take emissions under controls in building procurement contracts

0 2016 Ameer, B. [57] ja x x Impact of heavily subsidized energy prices for the

residential building sector in Kuwait: need to increase the electricity price to improve energy savings and efficiency in building

8

2016 Good, N. [58] ja x Techno-economic framework for the assessment of business cases of low carbon technologies, with a focus on multiple energy systems and vectors

19 2016 Krarti, M. [59] ja x x Analysis of the cost-effectiveness potential of net-zero

energy residential buildings in the Middle East and North Africa region, which is found to strongly depends on energy prices

11

2016 Brandão de Vasconcelos, A. [60]

ja x Cost-optimal analysis of several refurbishment scenarios accounting for different discount rate using sensitivity analysis

3 2016 Liu, H. [61] ja x Analysis of the impacts of technological advancement

on energy consumption in China’s building industry in light of the direct rebound effect

6 2016 He, L. [62] ja x Analysis to test the hypothesis that the relative energy

price and not the absolute one is the most important to explain energy consumptions

1 2017 Miezis, M. [63] cp x Algorithm for model predictive control (MPC) in

multi-family buildings, including energy prices as constraints, with application to a case study in Latvia

3 2017 Copiello, S. [1] ja x Review of the paradoxes affecting the research topics

focusing on building energy efficiency, one of which relates to the relationship between investments and energy prices

14

2017 Khabdullin, A.

[64] cp x Analysis of the possible use of electricity as a source for district heating systems considering electricity price in comparison with heat energy price

0 2017 Krarti, M. [65] ja x x Evaluation of economic and environmental impacts of

energy efficiency programs for new and existing buildings in Saudi Arabia under conditions of highly subsidized energy prices

1

2017 Weeber, M.

[66] cp x Overview and discussion of opportunities, risks, and trends associated with the topic of energy flexibility in a context of fluctuating energy prices

0 2017 Simona, P.L.

[67] cp x Study on increasing energy efficiency in collective residential buildings by acting on their thermal insulation

0 (1) ja: journal article; cp: conference paper; bc: book chapter.

(7)

Table 4. Summary of the results (fourth part). Economic parameter Year First author Venue

(1) Energy price Inflation rate Discount rate Topic Citations 2017 Di Giuseppe, E.

[68] cp x x Characterization of the stochastic inputs of a probabilistic Life Cycle Cost Analysis: inflation and discount rate are among the most influential parameters

0 2017 Dodoo, A. [69] ja x x Renovation of a multi-story residential building: real

discount rate and energy price increase have a significant impact on the cost-effectiveness and profitability of the measures

2

2017 Copiello, S. [5] ja x x x Life-Cycle Cost and Monte Carlo simulation: the discount rate is a prominent source of uncertainty and affects the results four times as much as the energy price

2

2017 Das, P. [70] ja x x Case-study retrofitting of Swedish attics: increments in energy costs and discount rates can impact the optimal design option

0 2017 Cui, T. [71] ja x Co-scheduling problem of Heating, Ventilation and Air

Conditioning (HVAC) and Hybrid Electrical Energy Storage (HEES) systems under dynamic energy prices

0 2017 Copiello, S. [4] ja x Analysis of building energy consumption: the role

played by both energy price and household income is worth attention with respect to the direct rebound effect

0

2017 Li, M.-J. [72] ja x Cointegration analysis of the relationship between energy consumption and its underlying explanations including energy price, economic development, and industrial structure

0

2017 Balin, A. [73] ja x Fuzzy multi-criteria decision making (MCDM) method to determine the best renewable energy alternatives for Turkey

4 2017 Zhang, Y. [74] ja x x Design of an integrated system including thermal

energy storage and building cooling, heating and power: its operation strategy highly depends on natural gas and electricity prices

1

2017 Lei, Y. [75] cp x Assessment of three residential space heating options: ground source heat pump, air source heat pump, and wall-hung gas boiler

0 2018 Dodoo, A. [76] ja x x Cost-effectiveness of the energy renovation measures

for a district heated building: the economic viability is sensitive to discount rates and energy price increase

0 2018 Agliardi, E. [77] ja x x x Techno-economic evaluation method for deep

renovation of buildings based on the real option theory, modeling energy price uncertainty through a mean-reverting stochastic process

0

2018 Liu, Y. [78] ja x x x Case study of cost-benefit analysis for energy retrofit of existing buildings: energy price is found to be the most sensitive factor

1 (1) ja: journal article; cp: conference paper; bc: book chapter.

The topics vary in a well-defined range. Several papers directly tackle problems related to energy prices and energy

supply costs. Earlier publications mostly address issues pertaining to energy policies and energy-related incentive

programs [

27,29,32,35-37], while recent documents, especially during the last decade, are more prone to focus their

attention on case studies, providing techno-economic analyses of investments in specific energy efficiency measures

and solutions [

14,38,42,44,46,58,60,67,69,70,75-78]. As far as those investments are concerned, the issue of

uncertainty is addressed [

5,41,48,68], and decision support systems are proposed [43,52,73]. The relationship between

the discount rate and the environmental aspects, notably greenhouse gas emissions, represents a kind of niche topic

among the analyzed studies [

49,56].

Building on a corpus of text data, namely the titles and abstracts of the examined publications, a co-occurrence

analysis of terms has been performed using the software VOSviewer [

79,80]. Recurring terms have been analyzed

according to a binary counting method; namely, only their presence does matter, while the overall number of their

occurrences is not considered. The minimum number of occurrences has been set to five, finding 69 terms that meet

the threshold. The resulting network representation (

Fig. 3

) considers the 60% most relevant items, hence 41 terms.

Fig. 3. Network representation of the co-occurrence analysis of terms.

Recognizing at least three significant fuzzy clusters of recurrent terms or expressions is possible. The first one (red

dots in

Fig. 3

) is arranged around the terms “development” (15 occurrences), “demand”, and “increase” (12

occurrences each). It is worthwhile to notice that the same cluster includes several other relevant terms, which

contribute to define its shape and boundaries. The focus is mainly on “energy efficiency improvement” and “energy

conservation” (six and seven occurrences, respectively), in buildings and specifically in the “residential sector”, with

a remarkable interest in “electricity” as an energy source and its price. The environmental concerns are subsumed

under to topic of “climate change”. The second cluster (blue dots in

Fig. 3

) features a core set made of few,

interconnected terms or expressions. The main term is “investment” (14 occurrences), which is also near to terms such

as “goal” and “decision”. Finally, the most representative terms and expressions of the third cluster (green dots in

Fig.

3

) are “energy saving” (16 occurrences) and “uncertainty” (13). The first item is near to “case study” analyses, wherein

the “discount rate” parameter (12 occurrences) is significant. The second item recalls other terms fitting the cluster,

such as “evaluation”, “sensitivity analysis”, and “simulation”. Within the cluster, a kind of subset refers to the “energy

service company”, often identified with the acronym “esco”, under the framework of “epc” which stands for energy

performance contracting.

Turning to the data sources, as well as to the estimates and the assumptions about the economic parameters, a

summary of empirical evidence is reported in

Table 5

. Concerning the historical series of energy prices and their

change rates, commonly used data source are IEA (International Energy Agency) and EIA (Energy Information

Administration).

(8)

Table 4. Summary of the results (fourth part). Economic parameter Year First author Venue

(1) Energy price Inflation rate Discount rate Topic Citations 2017 Di Giuseppe, E.

[68] cp x x Characterization of the stochastic inputs of a probabilistic Life Cycle Cost Analysis: inflation and discount rate are among the most influential parameters

0 2017 Dodoo, A. [69] ja x x Renovation of a multi-story residential building: real

discount rate and energy price increase have a significant impact on the cost-effectiveness and profitability of the measures

2

2017 Copiello, S. [5] ja x x x Life-Cycle Cost and Monte Carlo simulation: the discount rate is a prominent source of uncertainty and affects the results four times as much as the energy price

2

2017 Das, P. [70] ja x x Case-study retrofitting of Swedish attics: increments in energy costs and discount rates can impact the optimal design option

0 2017 Cui, T. [71] ja x Co-scheduling problem of Heating, Ventilation and Air

Conditioning (HVAC) and Hybrid Electrical Energy Storage (HEES) systems under dynamic energy prices

0 2017 Copiello, S. [4] ja x Analysis of building energy consumption: the role

played by both energy price and household income is worth attention with respect to the direct rebound effect

0

2017 Li, M.-J. [72] ja x Cointegration analysis of the relationship between energy consumption and its underlying explanations including energy price, economic development, and industrial structure

0

2017 Balin, A. [73] ja x Fuzzy multi-criteria decision making (MCDM) method to determine the best renewable energy alternatives for Turkey

4 2017 Zhang, Y. [74] ja x x Design of an integrated system including thermal

energy storage and building cooling, heating and power: its operation strategy highly depends on natural gas and electricity prices

1

2017 Lei, Y. [75] cp x Assessment of three residential space heating options: ground source heat pump, air source heat pump, and wall-hung gas boiler

0 2018 Dodoo, A. [76] ja x x Cost-effectiveness of the energy renovation measures

for a district heated building: the economic viability is sensitive to discount rates and energy price increase

0 2018 Agliardi, E. [77] ja x x x Techno-economic evaluation method for deep

renovation of buildings based on the real option theory, modeling energy price uncertainty through a mean-reverting stochastic process

0

2018 Liu, Y. [78] ja x x x Case study of cost-benefit analysis for energy retrofit of existing buildings: energy price is found to be the most sensitive factor

1 (1) ja: journal article; cp: conference paper; bc: book chapter.

The topics vary in a well-defined range. Several papers directly tackle problems related to energy prices and energy

supply costs. Earlier publications mostly address issues pertaining to energy policies and energy-related incentive

programs [

27,29,32,35-37], while recent documents, especially during the last decade, are more prone to focus their

attention on case studies, providing techno-economic analyses of investments in specific energy efficiency measures

and solutions [

14,38,42,44,46,58,60,67,69,70,75-78]. As far as those investments are concerned, the issue of

uncertainty is addressed [

5,41,48,68], and decision support systems are proposed [43,52,73]. The relationship between

the discount rate and the environmental aspects, notably greenhouse gas emissions, represents a kind of niche topic

among the analyzed studies [

49,56].

Building on a corpus of text data, namely the titles and abstracts of the examined publications, a co-occurrence

analysis of terms has been performed using the software VOSviewer [

79,80]. Recurring terms have been analyzed

according to a binary counting method; namely, only their presence does matter, while the overall number of their

occurrences is not considered. The minimum number of occurrences has been set to five, finding 69 terms that meet

the threshold. The resulting network representation (

Fig. 3

) considers the 60% most relevant items, hence 41 terms.

Fig. 3. Network representation of the co-occurrence analysis of terms.

Recognizing at least three significant fuzzy clusters of recurrent terms or expressions is possible. The first one (red

dots in

Fig. 3

) is arranged around the terms “development” (15 occurrences), “demand”, and “increase” (12

occurrences each). It is worthwhile to notice that the same cluster includes several other relevant terms, which

contribute to define its shape and boundaries. The focus is mainly on “energy efficiency improvement” and “energy

conservation” (six and seven occurrences, respectively), in buildings and specifically in the “residential sector”, with

a remarkable interest in “electricity” as an energy source and its price. The environmental concerns are subsumed

under to topic of “climate change”. The second cluster (blue dots in

Fig. 3

) features a core set made of few,

interconnected terms or expressions. The main term is “investment” (14 occurrences), which is also near to terms such

as “goal” and “decision”. Finally, the most representative terms and expressions of the third cluster (green dots in

Fig.

3

) are “energy saving” (16 occurrences) and “uncertainty” (13). The first item is near to “case study” analyses, wherein

the “discount rate” parameter (12 occurrences) is significant. The second item recalls other terms fitting the cluster,

such as “evaluation”, “sensitivity analysis”, and “simulation”. Within the cluster, a kind of subset refers to the “energy

service company”, often identified with the acronym “esco”, under the framework of “epc” which stands for energy

performance contracting.

Turning to the data sources, as well as to the estimates and the assumptions about the economic parameters, a

summary of empirical evidence is reported in

Table 5

. Concerning the historical series of energy prices and their

change rates, commonly used data source are IEA (International Energy Agency) and EIA (Energy Information

Administration).

(9)

Table 5. Summary of the results: sources, data, and assumptions. Year First author

and reference Sources Data and assumptions

2011 Ouyang, J. [14] Central Bank; National Bureau of Statistics;

Government data Inflation rate: 3%; Increase rate of electricity price: 2%; Discount rate: 6% 2012 Kumbaroglu,

G. [38] Historical time series (1999–2010) of real energy prices and price change rates Discount rate: 4.22% (estimates within the range 2.17-7.87%) 2013 Cajias, M. [39] German Investment Property Databank;

Federal Statistical Office

2013 Cox, M. [40] Energy Information Administration 2013 Egging, R. [41] Eurostat; Int. Energy Agency; Energy Inf.

Administration

2014 Deng, Q. [43] US Department of Energy; Energy

Information Administration

2014 Yan, X. [44] Central Bank; Government data; other

literature Discount rate: 9%

2014 Qian, D. [45] Yearbooks; other literature 2014 Bonakdar, F.

[46] National Energy Agency; other literature Energy price increase: 2%; Discount rate: 1%, 3%, 5%

2015 Wu, L. [49] Government data Discount rate: 6%

2015 Lin, B. [50] National Bureau of Statistics

2015 Deng, Q. [51] Government data; other agencies Energy price: $26.03/MMBTU; Discount rate (Expected return): 10%

2015 Deng, Q. [52] US Department of Energy

2015 Lin, B. [53] Yearbooks 2016 Lin, B. [54] Yearbooks 2016 Roshchanka,

V. [55] International Energy Agency; Government data Energy price: $0.087 per kWh (residential consumers) 2016 Ameer, B. [57] Government data; other literature Energy price: $0.007/kWh (residential

consumers); Discount rate: 5% 2016 Krarti, M. [59] Other literature Energy prices: 0.094 $/kWh and 0.162

$/m3; Discount rate: 5% 2016 Brandão de

Vasconcelos, A. [60]

Government data; other literature Discount rate: 3% (2-4% and 6%), 6% (5-7% and 10%)

2016 Liu, H. [61] Yearbooks

2017 Krarti, M. [65] Energy price: $0.05/kWh (residential

customer); Discount rate: 3% 2017 Di Giuseppe,

E. [68] Central Bank; Energy Inf. Administration; US Dept. of Energy Inflation rate: 1.9%; Interest rate: 4.09%

2017 Dodoo, A. [69] Energy price increase: 1%, 2%, 3%;

Discount rate: 1%, 3%, 5%

2017 Copiello, S. [5] Other literature Energy price 0.05-0.146€/kWh; Infl.: 0-4.5%; Discount rate: 0-15%

2017 Zhang, Y. [74] Central Bank; other literature Discount rate: 10%

2018 Dodoo, A. [76] Other literature Energy price increase: 1%, 2%, 3%; Discount rate: 1%, 3%, 5% 2018 Agliardi, E.

[77] Company data; other literature Energy price: 0,95€/m3; 0,18€/kWh; Inf: 8%; Interest rate: 3%

2018 Liu, Y. [78] Energy price increase: 5%, 10%, 15%,

20%

The other economic parameters are often estimated according to information conveyed by the National Institutes

of Statistics, Central Banks, and Governments. Sometimes, the estimates are integrated with data gathered from

specialized publications, such as various kind of yearbooks, or the previous literature. As regards the discount rate

parameter, levels of 3%, 5%, and 6% are common among the examined studies. However, it should be stressed that

the values above do not usually stem from the use of estimation methods such as the Capital Asset Pricing Model

(CAPM) or the Weighted Average Cost of Capital (WACC) [

81]. On the contrary, they are most of all assumptions

based on plausible ranges according to the pertinent literature.

4. Overview of the well-established research strands

Building on the bibliographic search above, there arise at least two significant research strands: the relationship

between energy prices and the profitability of efficiency-related investments is the former, the pivotal role played by

the discount rate when evaluating the investments in energy-efficient measures is the latter.

As far as energy prices are concerned, the reviewed literature points that more attention should be paid to the

following relationship: the lower the energy prices, the lower are the incentives to invest in energy efficiency

[

14,59,62,65,78]. That is a significant issue since energy prices are often lower than energy production costs, primarily

due to government subsidies [

27,30,37,50,57,61]. Besides, failing to address the uncertainty that is inherent in future

energy prices [

41,43,48,51,52] negatively affects efficiency-related investments [32,35,38].

A related issue may be described as follows. Energy efficiency investments are expected to reduce effective energy

prices. Cheaper energy sources - in relative terms, at least - lead to the substitution of input factors not only in

production processes and, ultimately, are likely to incentivize companies and households to adopt more

energy-intensive behavior [

53,54,61]. Therefore, the same energy efficiency investments are expected to disincentivize further

subsequent improvements [

1]. Accordingly, the literature highlights the importance of delving into the

substitute/complementary relationship between different energy sources [

34,74], the price elasticity of the demand for

energy [

4], and the demand-side management strategies and policies to improve energy efficiency [36].

With respect to the second research strand, the prominence of the discount rate in energy efficiency-related

evaluations is recognized by several authors, as it strongly affects the projected investments in energy-efficient

equipment and related energy consumptions [

40], the viability of the energy efficiency measures to be adopted

[

5,44,68-70,76], as well as the present value of the carbon cost factor used to account for climate externalities [49,56].

Some authors draw explicitly the conclusion that investment in energy efficiency solutions and low discount rates go

hand in hand [

60].

5. Conclusions

The corpus of literature on building energy efficiency is steadily growing starting from, at least, the oil shocks of

the seventies. Accordingly, the need for a systematization of knowledge is perceived to have increased in recent years.

Under the above framework, this study performs a literature review adopting a specific focus. The central question it

tries to answer is as follows: how the research on building energy efficiency deal with three economic parameters,

namely, the energy price, the energy inflation rate, and the discount rate. A total of 65 publications have been analyzed

with regard to the issues they address, the commonly used data sources, the estimates and assumptions. As far as the

topics are concerned, a representation of the primary items, their clusters, and the network relationships stems from a

co-occurrence analysis of terms. Moreover, two well-established research strands have been identified. The first

concerns the energy price parameter and its relationships with the willingness to adopt energy efficiency solutions.

The second refers to the role played by the discount rate parameter, which is likely to strongly affect the economic

viability of the investments in efficiency-related measures and solutions.

It is worthwhile to stress some limitations of this study, which pave the way to further developments. In particular,

the number of analyzed documents is somewhat limited by some choices that drive the literature search. On the one

hand, the data source is the abstracting and indexing Scopus, while other similar services are not considered. On the

other hand, the search keys concerning the three economic parameters - namely, energy price, inflation rate, and

discount rate - are searched only in the titles and abstracts, not in the full text. Although there are appropriate reasons

for those choices, as discussed in the previous section 2, they are also likely to shorten the list of results. Therefore,

the literature review presented here lends itself to be expanded, which is expected to strengthen further the empirical

findings discussed so far.

Figura

Fig. 1. Growing interest for building energy efficiency (source: Google Ngram Viewer)
Fig. 2. Summary of the bibliographic search in Scopus.
Fig. 2. Summary of the bibliographic search in Scopus.
Fig. 3. Network representation of the co-occurrence analysis of terms.
+2

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